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[P] Artificial Neural Networks and prediction (Scilab)

I have ANN Toolbox for Scilab and some script which I do not understand completely. I studied that at least 8 years ago but don’t remember much. What I need is help understanding the script and making few changes to it. The main thing I would like to see is correct chart for the computations. The code:

clear clc // data X = [1.00 2.00 3.00 2.00 3.00 4.00 3.00 4.00 5.00 4.00 5.00 6.00 5.00 6.00 7.00 6.00 7.00 8.00]; // libraries exec("ann_FF_init.sci"); exec("ann_FF_Mom_online.sci"); exec("ann_d_sum_of_sqr.sci"); exec("ann_d_log_activ.sci"); exec("ann_FF_run.sci"); exec("ann_log_activ.sci"); // k - predicition range? k=2; // data rows and cols count [rows,cols]=size(X); // normalize the learning data - what it does? makes values in range from 0.00 to 1.00? for i=1:cols X(:,i)=X(:,i)/sqrt(X(:,i)'*X(:,i)); end; // learning series, pair <U,Z>, automatic conversion of X which is a column - what happens here? U=[]; Z=[]; for i=1:rows-k-1 U=[U X(i:i+k-1)]; Z=[Z X(i+k)]; end; // NN structure [in_count, pattern_count]=size(X); [out_count, pattern_count]=size(Z); // neurons count in layers N=[in_count 10 7 out_count]; r=[0,1]; rb=[0,1]; // initialize W=ann_FF_init(N,r,rb); // learning parameters lp=[0.1 0.05 0.5 0.1]; lp=[0.1 0.05 0.5 0.1]; // epochs count T=12000; 500 for testing epochs=500; // learning; X/x = training, Z/t = output, N = architecture, W = init weights, lp = learning rate, epochs/T = iterations [W,sW]=ann_FF_Mom_online(X,Z,N,W,lp,epochs); // full run Y=ann_FF_run(X,N,W); // show data - which are what? //Z' //disp(Y); //(Y-Z)' // plot data - how to plot input? how to plot prediction correctly? //plot(X); //plot(Y,"r"); //plot(Z); 

The questions I have given in the code. Can anyone explain me the script?

submitted by /u/discl0se
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Toronto AI is a social and collaborative hub to unite AI innovators of Toronto and surrounding areas. We explore AI technologies in digital art and music, healthcare, marketing, fintech, vr, robotics and more. Toronto AI was founded by Dave MacDonald and Patrick O'Mara.